Accredited official statistics

Social housing lettings in England, technical notes: April 2022 to March 2023

Updated 6 March 2024

Applies to England

1. Introduction

The “Social Housing Lettings in England” statistical series has been badged as Accredited Official Statistics^{[footnote 1]}, the quality mark of government statistics, following assessment by the UK Statistics Authority in 2014. We abide by the standards of trustworthiness, quality and value in the Code of Practice for Statistics from data collection through to publication.

2. Data collection

Information for the 2022/23 release reflects data given by providers for the financial year ending 31 March 2023. CORE has been a requirement on the Single Data List for local authorities since 2010 and is a regulatory requirement of the social housing regulator for private registered providers.  

Statistics presented in this release are based on the data submitted through the online Continuous Recording system (CORE) by private registered providers and local authorities. CORE was first set up in 1989 for PRPs and its remit expanded to local authorities in 2004.

Data providers complete a range of information set out in a form about tenants that are accessing social housing and the property they are letting. Practice varies in terms of how local authorities and housing associations collect and compile the data that is submitted on the CORE form. Some questions are answered with information recorded at the point of registration, other elements about the type of tenancy and stock are drawn from the providers’ own housing management information system, with the remaining CORE-specific questions are asked of tenants by housing officers at sign-up.

Once complete, the CORE logs are input online, either manually or directly from their internal systems via a bulk upload. The data are initially validated at the point of entry as they are submitted by data providers, and then undergo further validation and quality assurance processes. These processes are described in the “Data Quality” section.

3. Data quality

3.1 Collection method

CORE data is collected from housing providers – both local authorities (commonly called ‘council housing’) and private registered providers (commonly called ‘housing associations’).

CORE data comprises three key themes: information about the tenants, tenancies, and properties.

Housing providers are the direct creators (and holders) of the information about tenancies and properties. Often, they need this information themselves for day-to-day management of their stock and lettings. By collecting this data from housing providers, we are collecting data directly from the source.

Some information about the tenant can only be answered by the tenant themselves, e.g. self-reported reason for leaving last settled home. Whilst ideally we would collect this information directly from the tenant, central government has no existing interface with tenants when they get a new social housing let. Since housing providers have at least one face to face interaction with tenants and housing providers also hold the information we require on tenancies as properties, the most efficient method to collect the CORE-specific tenant questions is for housing providers to ask tenants at sign-up, i.e. when tenants move into the property.

3.2 Coverage

The data collected through CORE differs from the social housing data in the Local Authority Housing Survey (LAHS) in that CORE is a ‘flow’ measure of all new social housing lettings which records data at case level (i.e. individual lettings), whereas data in LAHS is a ‘stock’ measure of all social housing stock in local authorities. Some LAHS information is presented in this release to provide context to the information from CORE on new lettings. Technical notes are available at: https://www.gov.uk/government/statistics/local-authority-housing-statistics-technical-notes-2021-to-2022.

The English Housing Survey (EHS) also provides social housing lettings data but the statistics are based on a survey and are again a ‘stock’ measure of social housing stock. CORE data focuses on the tenancy details at the point of letting, and besides property characteristics also collects information on the socio-demographic profile of the household, their housing circumstances and some financial information. CORE does not record any information of social housing lettings that are continuing – only new lettings.

CORE lettings data are reported by all registered providers, and voluntarily by those who are not registered with the  Regulator of Social Housing for new lettings only. Information is collected for General Needs and Supported Housing, for Social Rent, Affordable Rent and Intermediate Rent, by financial year.

Some types of lettings are excluded from CORE, including:

• Mutual exchanges (where tenants have swapped homes)

• Conversions of starter or introductory tenancies to assured or secure tenancies (because the introductory tenancy will have previously been reported to CORE)

• Successions by assignment (where the tenancy has transferred to another person at the request of the sole tenancy)

• Social Rent or Affordable Rent General Needs lettings on a fixed-term basis for less than two years (these are deemed temporary housing)

3.3 Completeness of CORE data

CORE is designed to be a complete census of new social housing lettings provided by local authorities and private registered providers that own social housing stock.

Whilst data providers should submit data for all new social housing tenancies, this does not always happen in practice. In addition, not all questions are compulsory so information may be incomplete for some tenancy records. This may introduce bias into the end statistics. We minimise this by applying weighting and imputation processes.

Weighting is applied at case level (i.e. for individual lettings) to adjust for non-response by local authorities.

Imputation is applied at item level (i.e. for individual questions within a letting log) to compensate for question non-response. This is done for both local authorities and private registered providers.

Local authority weighting

Local authority weights are calculated by comparing the total number of lettings in that area reported to the Department’s Local Authority Housing Statistics (LAHS) return.

Weights are calculated for groups of similar local authorities, where these groups are defined by the ONS UK area classifications. For each of the 13 groups, the weight is calculated for all responding local authorities as the ratio of the number of lettings judged to be the most reliable (either reported to LAHS or reported to CORE), relative to those reported to CORE.

Currently weights are not calculated for private providers as response is high and there is no alternative data source robust enough to be used for CORE weighting purposes. For instance, whilst the Statistical Data Return (SDR) published by the Regulator for Social Housing holds includes the number of lettings by private registered providers, the Regulator’s coverage is different to that of CORE. We will continue to review this assumption over time.

Weights are only suitable for use when conducting analysis at the national level. When conducting analysis on sub-national geographies such as local authority areas the weights should not be used. Summing sub-national figures will not give a true figure for the England total, as the national figure should be calculated separately using weights.

Imputation of missing items

Some of the questions on the CORE questionnaire are not compulsory. In particular, data on household characteristics may not be available to the housing officer or the tenant may prefer not to answer. In these cases, we impute responses.

Our imputation methods are based on the recommendations of the ONS Methodology Advisory review in 2013. We follow a ‘nearest neighbour’ or ‘donor imputation’ approach, a standard statistical technique. This involves identifying records that are similar to the records with missing data, based on variables that have been determined to be of most importance (e.g. other demographic characteristics, geography etc.). The algorithm randomly chooses a record (the ‘donor record’) from the set of records with the closest data for the non-missing variables and copies the data for the missing variables from the donor record into the record with missing data.  

The imputation process uses ONS UK area classifications to group local authorities into clusters – one of the variables used to judge lettings’ similarity. The imputation is carried out separately for General Needs and for Supported Housing and separately for the different rent types, to reflect the different demographic profiles of their tenants.  

Imputation is done one variable at a time on the missing variables for the lead tenant in the following order: age, gender, economic status, nationality and then ethnicity. In most cases the imputation methodology prevents using donor data that would normally fail the usual validation process.

We impute the following demographic variables for the lead tenant:

• Age

• Gender

• Economic status

• Ethnicity

• Nationality

Income data is not imputed. Income has a higher non-response rate and as the rate is uneven across household types any imputed results may lead to biased estimates. Instead, to improve completeness of income data the department is working with data providers to encourage a higher response rate.

3.4 Derived Variables

In addition to the information given by providers for new social lettings additional variables are created for each log using the existing information. Some are simple, for example weekly rent and weekly income values are derived from their equivalent base values and their frequencies. More complicated derived variables are described below.

Vacant days

The vacant days refers to the number of days an existing social property was available to let before the start date of the new tenancy.

The vacant days calculation uses the void date, the major repairs completion date (if relevant) and the start date of the new letting. All of these dates are collected in the CORE form.

The void date is the date the property was (legally or contractually) available to let, or for:

• re-lets: the day after the previous tenant’s contract ended

• new builds: the day the landlord legally first owned the property (‘completion date’)

• new conversions or acquisitions: completion date, or the day after rehabilitation work ended

• new leases: the day the landlord got contractual property rights and could let it out to tenants

The major repairs completion date is the date when any works that could not be reasonably carried out with a tenant living at the property were completed. For example, structural repairs.

The vacant days is the difference between the void date and the start date of the new letting. If the property underwent major repairs, the number of vacant days is the difference between the major repairs completion date and the start date of the new letting.

For example, for a letting that had a void date of 07/12/2023, a major repair completion date of 17/12/2023 and a tenancy start date of 18/12/2023 then the vacant days will be 1. If this letting had no major repairs (so no major repair date) then the vacant days would be 11.

Bedroom standard

The bedroom standard is a measure of whether a property is of an “appropriate” size for the household. The definition is set out in law^{[footnote 2]}.   Comparing the derived bedroom standard for a household with the number of bedrooms in the property of their new let shows whether the household has been allocated a property that is “too small”, “too big”, or “of the appropriate size”.

The derivation for bedroom standard uses the age, gender and relationship to lead tenant of all household members, which are collected in the CORE form.

If the lead tenant answered ‘prefers not to say’ for age or gender then the imputed versions are used. If any of the other household members answer age, gender or relationship to the lead tenants with ‘prefers not to say’ then the bedroom standard is not calculated and the variable is left blank.

The bedroom standard is calculated, according to law, by allocating a separate bedroom to each:

• adult couple

• any remaining adult (aged 21 years or over)

• two adolescents (aged 10 to 20 years) of the same sex

• one adolescent (aged 10 to 20 years) and one child (aged 9 years or under) of the same sex

• two children (aged 9 years or under) regardless of sex

• any remaining child (aged 9 years or under)

For example, a couple with children of different sexes and less than 9 years old would be assigned two bedrooms, whereas if one of the children was older than 9 years then the household would be assigned 3 bedrooms.

For years where self-reported gender as opposed to biological sex were collected (2019/20 onward) the bedroom standard has been calculated using self-reported gender. When calculating the bedroom standard for these years where sex is involved in room sharing (for example adolescents sharing a room) those identifying as “Other” are only assumed to share a room with another household member identifying as “Other”.

Household composition

The household composition variable is a summary descriptor of a household, such as elderly couple. In CORE the same derivation is used as in other housing data sources, such as the English Housing Survey, to aid cross-comparison.

Household composition is derived from household members’ ages, genders, and relationship to the lead tenant, which are collected in the CORE form.

If the lead tenant answered ‘prefers not to say’ for age or gender then the imputed versions are used. If any of the other household members answer age, gender or relationship to the lead tenants with ‘prefers not to say’ then the household composition is not calculated and the variable is left blank.

Where household composition is calculated the following process takes place in the given order:

• If the ages of either the lead tenant or the second household member are 60 and over, the relationship between the second household member and the lead tenant is “Partner” and there are only two household members then the household composition is “Elder couple”

• If the age of the lead tenant is over 60 and there is only one household member then the household composition is “Single elder”

• If the age of the lead tenant is over 16, one member of their household has the relationship of “Partner” and one or more members have the relationship “Child” then the household composition is “Couple with child(ren)”

• If the age of the lead tenant is over 16, one member of their household has the relationship of “Partner” and there are only two household members then the household composition is “Couple”

• If the gender of the lead tenant is male, and they are 16 or over, the number of household members with a relationship of “Child” is greater than 0 and the number of household members with other relationships (“Partner” or “Other”) is 0 then the household composition is “Single male with child(ren)”

• If the gender of the lead tenant is female, and they are 16 or over, the number of household members with a relationship of “Child” is greater than 0 and the number of household members with other relationships (“Partner” or “Other”) is 0 then the household composition is “Single female with child(ren)”

• If the gender of the lead tenant is male, the lead tenant is 16 or over and there is only one household member then the household composition is “Single male”

• If the gender of the lead tenant is female, the lead tenant is 16 or over and there is only one household member then the household composition is “Single female”

• If the household hasn’t been assigned a composition by this point then they are “Other”

Income

Income is collected at a household level. It includes income after tax from employment, pensions, Universal Credit and child benefit. It excludes National Insurance (NI) contributions, tax, housing benefit and council tax support. The child benefit element of income is not collected in CORE and instead derived using the ages of household members, their relationships to the lead tenant and their economic status.

Income is an optional question. In 2022/23 income was missing for 58% of lettings logs. The response rate differs by needs type, rent type and provider type. Exact figures are available in table 4b of the Data Quality tables, available from the same page as these Technical Notes. We do not impute income because of the uneven response rate from different household types which may cause imputed results to have biased estimates.

Rent burden  

Rent burden is the proportion of a household’s income that is spent on rent and eligible service charges.

We can therefore only calculate a household’s rent burden in cases where they have answered the question on income. In 2022/23 this was 42% of lettings. Rent and eligible service charges are mandatory questions so the data is complete.

Households may receive Universal Credit or housing benefit to help pay their rent and specific eligible charges.

Our definition of income (see ‘Income’ above) includes Universal Credit as this is paid directly to the tenant. This means that the money to pay their rent is included in the income figure collected in CORE.

However, our definition of income excludes housing benefit as this is paid directly to the landlord. This means that for households on Universal Credit the money to pay for their rent isn’t included in the income figure reported to CORE.

In order to calculate rent burden in a consistent way, for households who receive housing benefit we estimate the amount of housing benefit paid and add that to the collected income figure. Prior to 2022/23, this was calculated by estimating the amount that the household is eligible for based on the number of bedrooms in the property, the weekly rent and eligible service charges and the ages, relationships and economic statuses of the individual household members. Housing benefit is reduced for any non-dependent household members based on their individual incomes. As we do not collect data on income for individual household members, we made assumptions about what their income might be based on their economic status. As we also needed to know the number of bedrooms in the property and that is not collected for Supported Housing we were unable to calculate rent burden for Supported Housing lettings using this method.

We are proposing moving to a new methodology for calculating housing benefit from 2022/23. This uses information from the question on the CORE form: ‘after the household has received any housing-related benefits, will they still need to pay for rent and charges?’. If the answer to this question is ‘no’, then the amount of housing benefit the household receives is equal to the total of the rent and eligible service charges. If the answer is ‘yes’, then the tenant also provides the outstanding amount, and we therefore calculate the amount of housing benefit received as the total of the rent and eligible service charge minus the outstanding amount.

Adopting this new methodology means we are able to make fewer assumptions about the household’s situation. We can also now calculate rent burden for Supported Housing lets as we do not need to know the number of bedrooms to calculate our estimate. Table 4e in the Data Quality Tables section of this release contains data on completion rates for both the existing and proposed methods of calculating rent burden. This can be found at the same page as these Technical Notes.

For example, consider a household where the lead tenant lives with their adult son,  they both work part-time and have a combined household income of £25,000, all of which is collected on the CORE form. The lead tenant’s son would be classed as a non-dependent when claiming housing benefit, and a deduction would be calculated based on the son’s weekly earnings. The original method of estimating housing benefit would require us to calculate the size of this deduction. We cannot do this accurately as we only have household income, not the son’s earnings.

Another example of where the original method requires assumption centres on pension age. There are higher rates of housing benefit available to people who reached pension age prior to 1 April 2021. However, whilst we collect the age of the lead tenant, we do not know their date of birth and cannot therefore know if they are eligible for this.

A final example is that there are a range of premiums for carers and people with disabilities. We do not collect information on whether someone is a carer. The information we collect about disabilities and long-term sickness in CORE is at the household level, not at the person level. This means we are unable to determine whether the household is eligible for any of the premiums for carers and people with disabilities using the information collected in CORE.

Quality assurance procedure

4. Users and uses

CORE is a unique source of information in providing detailed information about individual tenancies. No other existing data source, either published or held internally by governmental or other central bodies, contains the breadth of information collected by CORE. It is the only census of all new lettings in England, the only data source across the social housing sector collected at individual tenancy level and the only source that allows detailed multivariate analysis of household and dwellings in the social sector. Social housing lettings statistics and the underlying CORE datasets inform national housing policy in areas such as social housing allocation policy, homelessness reduction and as part of the evidence base for the Domestic Abuse Bill. Data on housing costs, housing-related benefits and affordability is used to inform modelling on the value for money and societal impact of investment into new affordable housing, e.g. via the Affordable Homes Programme. The Department uses CORE data on demographics of households in new social lettings to inform equality impact assessments, e.g. for changes to eligibility requirements following the UK leaving the European Union.

CORE data is also used to fulfil the Department’s parliamentary scrutiny obligations through Parliamentary Questions (PQs) and to meet government transparency aims through Freedom of Information requests.

The Department’s Arms’ Length Bodies use CORE data in order to carry out their functions. For example, Homes England use the data to monitor government investments and schemes, and the Regulator of Social Housing use CORE data in their regulatory activities.

Other government departments also use CORE data. For example, CORE data is a component of the key government inflation measure – the Retail Price Index (RPI) published by the Office for National Statistics (ONS). Another example is our collaboration with the Ministry of Defence (MoD) on social housing provision for armed forces personnel to inform their Armed Forces Covenant which aims to ensure members of the Armed Forces are not disadvantaged in their access to government-provided services.

Social housing providers use the data to understand the market for social housing and benchmark their own performance. Local government also use the data to inform their Strategic Housing Market Assessments that form part of the National Planning Policy Framework.

Academics, researchers, charities and the wider public use these statistics to understand social housing issues. Some of these users also use the underlying administrative data available at the UK Data Archive.

5. Data protection and confidentiality

Since the introduction of the General Data Protection Requirements (GDPR) on 25 May 2018 updates have been made to how data are submitted into the CORE system:

• Data sharing agreement – all CORE data providers must sign a formal data sharing agreement with DLUHC;

• CORE data protection officer – all CORE data providers must set up a CORE data protection officer on the CORE system to electronically sign the data sharing agreement on behalf of their organisation;

• Privacy notice – a new CORE privacy notice must be made available to all new social housing tenants when their data are collected which informs tenants why their data is being collected, how it is used and how their confidentiality is protected.

All of these steps must be taken for an organisation to submit data into CORE. This ensures that tenants are informed of how their data will be used and that it is being processed securely.

Our disclosure policy is applied to all internal and external uses of the data, including this statistical release and accompanying products.

Case level data sets are available to researchers and the public through the UK Data Archive via one of three types of licence agreement with different levels of data protection to meet different user needs whilst maintaining tenant confidentiality in line with legislation.

The Department shares case level data with a small number of other governmental bodies, e.g. the Regulator for Social Housing, as detailed in our privacy notice. All aspects of data protection legislation are followed, including ensuring legal justification, minimising the number of data items shared, and putting appropriate processes in place for sharing and storing the data.  

6. Revisions policy

This policy has been developed in accordance with the UK Statistics Authority Code of Practice for Official Statistics and the Department‘s Revisions Policy:

1. Non-scheduled revisions: These are where a substantial error has occurred as a result of the compilation, imputation or dissemination process. Revised products are released as soon as is practicable, alongside an explanatory note on both the cause and impact of the error. Data are clearly indicated in tables as ‘provisional’ (P) or ‘revised’ (R).

2. Scheduled revisions: Providers cannot retrospectively submit or revise data after the close down deadline date for the re-porting year. The only scheduled revision is to the weights, currently based on provisional LAHS data, once the final LAHS data are published. Revised weights and estimates are made in the subsequent release in the historic tables.

For example, 2021/22 weights were revised after the publication of final LAHS 2021/22 data in summer 2022. The summary tables published as part of the 2022/23 Social Housing Lettings release use the revised weights for the 2021/22 figures in the time series tables.  

7. Related statistics

7.1 Social housing sales data

The Department’s Social Housing Sales and Demolitions in England statistical series utilises data collected through CORE for sales of self-contained dwellings and re-sales of any part-owned dwellings (shared ownership) from private registered providers. They are available from:

https://www.gov.uk/government/collections/social-housing-sales-including-right-to-buy-and-transfers

7.2 Housing stock in England

The Department publishes annual live tables on housing stock and vacancies by tenure at:

https://www.gov.uk/government/statistical-data-sets/live-tables-on-dwelling-stock-including-vacants#live-tables

7.3 Private registered provider social housing

The Regulator for Social Housing in England, the separate statutory regulatory body, publishes its annual Statistical Data Return (SDR) including the total number of social and affordable lettings and stock, is based on data collected from private registered providers. They are available from:

https://www.gov.uk/government/statistics/private-registered-provider-social-housing-stock-and-rents-in-england-2022-to-2023

7.4 Local authority housing social housing

The Department’s annual Local Authority Housing Statistics (LAHS) data return reports on a wide range of housing related data including total dwellings, lettings and vacant stock, waiting lists, rents, and condition of stock^{[footnote 3]} , available from:

https://www.gov.uk/government/collections/local-authority-housing-data

7.5 English Housing Survey (EHS)

The Department’s annual English Housing Survey (EHS) providing information on the quality and quantity of both social and non-social stock in England based upon a sample of households is at:

https://www.gov.uk/government/collections/english-housing-survey

7.6 Homelessness

The Department’s statistics relating to homelessness include quarterly Statutory Homelessness and the annual Rough Sleeping in England, both available from:

https://www.gov.uk/government/collections/homelessness-statistics

7.7 Devolved administrations

The devolved administrations of the UK produce and publish their own social housing lettings and sales statistics. These data are not published alongside the England statistics in this release because there are not directly comparable figures across the country due to differences in data collection methodologies and policies.

Wales

• Social housing stock and rent statistics:

https://gov.wales/social-landlord-housing-stock-and-rents

• Social housing lettings statistics:

https://gov.wales/data-collection-social-housing-lettings

Scotland

• Local authority social lettings:

http://www.gov.scot/Topics/Statistics/Browse/Housing-Regeneration/HSfS/Lettings

• Social sector summary tables: http://www.gov.scot/Topics/Statistics/Browse/Housing-Regeneration/HSfS/socialhousing

• Private registered provider social lettings: http://www.gov.scot/Topics/Statistics/Browse/Housing-Regeneration/HSfS/Improvements

Northern Ireland

• Social housing allocations data: https://data.nisra.gov.uk/table/SHALGD

8. User engagement

Users are encouraged to provide feedback on how these statistics are used and how well they meet user needs. Comments on any issues relating to this statistical release are welcomed and encouraged. For this year any views on the rent burden methodology change are particularly welcomed. Please contact CORE@levellingup.gov.uk.  

9. Enquiries

Media enquiries:

Office hours: 0303 444 1209

Email: NewsDesk@levellingup.gov.uk

Public or statistical enquiries:

Email: CORE@levellingup.gov.uk

10. Footnotes

1. Accredited official statistics are called National Statistics in the Statistics and Registration Service Act 2007. Further details can be found on the Office for Statistics Regulation website. ↩

2. Housing Act 1985. ↩

3. Prior to 2011/12 much of this information was collected through the department’s Housing Strategy Statistical Appendix (HSSA). ↩